Abstract
We describe the architecture of the parallel management kernel for the parallel inference engine PIE64, focusing on how to treat load distribution and scheduling in highly parallel symbolic processing. Since the kernel manages automatic load distribution and scheduling, the task remaining for the programmer is to employ parallel algorithms with sufficient concurrency. A programmer need no longer be concerned with load distribution, load partitioning, load assignment, parallelism explosion, exhaustion of resources, or execution efficiency. We also describe an evaluation of the load distribution method.
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